Stochastic Stability of Discrete-time Phase-coupled Oscillators over Uncertain and Random Networks

Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods

Capturing the uncertainty about a sudden change in the properties of time series with confidence curves

Modeling Pedestrian Tactical and Operational Decisions Under Risk and Uncertainty: A Two-Layer Model Framework

Abstracting the Traffic of Nonlinear Event-Triggered Control Systems

Adaptive Prescribed Performance Asymptotic Tracking for High-Order Odd-Rational-Power Nonlinear Systems

Robustness Analysis of Platoon Control for Mixed Types of Vehicles

Discrete-Time Fractional-Order Dynamical Networks Minimum-Energy State Estimation

Impact of Leader-Follower Behavior on Evacuation Performance: An Exploratory Modeling Approach

Real-Time Train Scheduling With Uncertain Passenger Flows: A Scenario-Based Distributed Model Predictive Control Approach

Promises of Deep Kernel Learning for Control Synthesis

Formal Abstraction of General Stochastic Systems via Noise Partitioning

Use of confidence curves to represent uncertainty in hydro-meteorological time series analysis

Probabilistic Risk Metric for Highway Driving Leveraging Multi-Modal Trajectory Predictions

Robust Optimal Control for Demand Side Management of Multi-Carrier Microgrids

Technological Uncertainty and Standardization Strategies: A Coopetition Framework

Online Multi-Robot Task Assignment with Stochastic Blockages

Distributionally Robust Optimization via Haar Wavelet Ambiguity Sets

Uncertain uncertainty in data-driven stochastic optimization: towards structured ambiguity sets

On Learning Discrete-Time Fractional-Order Dynamical Systems